SKILLEMALL.ai

AD hubo

Implements and tests code while an independent reviewer challenges every change until all findings are reconciled. Use only when the user explicitly invokes, selects, or mentions Hubo for a programming task.

ClawHub Agent Skills author: Hongchao Liu v0.4.5 MIT-0 5 files body ≈ 310 tokens Open the sourceclawhub.ai analyzed 3 d ago

Implements and tests code while an independent reviewer challenges every change until all findings are reconciled.

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerSoftware developmentFinanceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50Steps. 2 steps
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 310 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +4Structure: 1 headings, hard to scan
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 207: enough signal without eating the budget
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: clean
    Hubo is a disclosed multi-agent coding workflow that requires explicit user activation and keeps its file-editing and review roles purpose-aligned.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026